Understanding and operating an oil and gas production asset as a single holistic system has been frustrated by significant impediments. For any asset, there are typically multiple applications, multiple data sets, multiple taxonomies and multiple stakeholders, some or all of which may be sharing common data across the asset. Interoperability among these programs, persons, and structures as a single system, while desired, has been frustrated by the lack of an underlying framework for handling the necessary transformations, translations, and definitions required between and among the various system components.
Attempts to provide this understanding and operation have previously focused on providing data replication, where each stakeholder group develops or receives its own version of the logical network and data model that includes all of its requirements. In these attempts, the act of transforming the data model by correlating changes between the data model representations has not been done or has been done crudely. Although some level of interoperability has been achieved by point to point integration, it is largely limited to supporting single workflows. Moreover, changes to the data model representations cannot be effectively controlled when each stakeholder can decide whether such changes should be applied (accepted) and communicated to the other stakeholders. Previous approaches thus, have been unable to account for reconciliation and data integrity issues in a systematic and/or system-wide way.
There is therefore, a need for systems and methods that provide uninterrupted interoperability among the various data sets, applications, taxonomies and stakeholders sharing data across a production asset. In other words, there is a need for transforming a system model by correlating only approved manipulations of meta-data model representations and asset-logic model representations in the system model.